The amount of data generated in large clinical and phenotyping studies that use single-cell cytometry is constantly growing. Recent technological advances allow the easy generation of data with hundreds of millions of single-cell data points with >40 parameters, originating from thousands of individual samples. The analysis of that amount of high-dimensional data becomes demanding in both hardware and software of high-performance computational resources. Current software tools often do not scale to the datasets of such size; users are thus forced to downsample the data to bearable sizes, in turn losing accuracy and ability to detect many underlying complex phenomena.

中文翻译：

---

GigaSOM.jl：大型细胞计数数据集的高性能聚类和可视化


使用单细胞细胞术的大型临床和表型研究产生的数据量不断增长。最近的技术进步使得可以轻松生成来自数千个单独样本的数亿个单细胞数据点和超过 40 个参数。对大量高维数据的分析对高性能计算资源的硬件和软件都提出了要求。当前的软件工具通常无法扩展到如此大小的数据集；因此，用户被迫将数据采样到可以承受的大小，从而失去了检测许多潜在复杂现象的准确性和能力。